A type directed translation of MLF to system F

LeijenDaan,

doi:10.1145/1291220.1291169

Cited by 5 publications

(12 citation statements)

References 11 publications

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“…MLF [10] (sometimes stylised as ML F ) is considered to be the most expressive of the conservative ML extensions so far. MLF achieves its expressiveness by going beyond regular System F types and introducing polymorphically bounded types, though translation from MLF to System F and vice versa remains possible [10,11]. MLF also extends ML with type annotations on lambda binders.…”

Section: Related Workmentioning

confidence: 99%

“…• Predictable behaviour Our ideal solution would avoid guessing polymorphism and be specified so that programmers can anticipate where type annotations will be needed. More recent systems, such as HMF [11] and GI [24], use System F types, and are relatively easy to implement, but employ heuristics to guess one of several different polymorphic types, and require programmer annotations if the default heuristic behaviour is not what is needed.…”

Section: Introductionmentioning

confidence: 99%

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FreezeML: Complete and Easy Type Inference for First-Class Polymorphism

Emrich,

Lindley,

Stolarek

et al. 2020

Preprint

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ML is remarkable in providing statically typed polymorphism without the programmer ever having to write any type annotations. The cost of this parsimony is that the programmer is limited to a form of polymorphism in which quantifiers can occur only at the outermost level of a type and type variables can be instantiated only with monomorphic types.Type inference for unrestricted System F-style polymorphism is undecidable in general. Nevertheless, the literature abounds with a range of proposals to bridge the gap between ML and System F.We put forth a new proposal, FreezeML, a conservative extension of ML with two new features. First, let-and lambdabinders may be annotated with arbitrary System F types. Second, variable occurrences may be frozen, explicitly disabling instantiation. FreezeML is equipped with type-preserving translations back and forth between System F and admits a type inference algorithm, an extension of algorithm W, that is sound and complete and which yields principal types.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

FreezeML: Complete and Easy Type Inference for First-Class Polymorphism

Emrich,

Lindley,

Stolarek

et al. 2020

Preprint

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“…We first define a minimal imperative language (Section 6.1) and then present ML-style functional pseudocode for converting any program written in this language into a PEG (Section 6.2). Next, we present a formal account of the conversion process using type-directed translation rules in the style of [37] (Section 6.3). Finally, we outline a proof of the semantic preservation of the translation (Section 6.4).…”

Section: Definition 52 (Invariance Predicate)mentioning

confidence: 99%

“…Type-directed translation. In this section we formalize the translation process described by the pseudo-code implementation with a type-directed translation from SIMPLE programs to PEGs, in the style of [37]. The type-directed translation in Figure 17 is more complicated than the implementation in Figure 15, but it makes it easier to prove the correctness of the translation.…”

Section: Statementsmentioning

confidence: 99%

Equality Saturation: A New Approach to Optimization

Tate¹,

Stepp²,

Tatlock³

et al. 2011

Logical Methods in Computer Science

131

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Abstract. Optimizations in a traditional compiler are applied sequentially, with each optimization destructively modifying the program to produce a transformed program that is then passed to the next optimization. We present a new approach for structuring the optimization phase of a compiler. In our approach, optimizations take the form of equality analyses that add equality information to a common intermediate representation. The optimizer works by repeatedly applying these analyses to infer equivalences between program fragments, thus saturating the intermediate representation with equalities. Once saturated, the intermediate representation encodes multiple optimized versions of the input program. At this point, a profitability heuristic picks the final optimized program from the various programs represented in the saturated representation. Our proposed way of structuring optimizers has a variety of benefits over previous approaches: our approach obviates the need to worry about optimization ordering, enables the use of a global optimization heuristic that selects among fully optimized programs, and can be used to perform translation validation, even on compilers other than our own. We present our approach, formalize it, and describe our choice of intermediate representation. We also present experimental results showing that our approach is practical in terms of time and space overhead, is effective at discovering intricate optimization opportunities, and is effective at performing translation validation for a realistic optimizer.

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“…We omitted the proof of inclusion from xMLF into F x ι by lack of space, but also because it resembles theirs. In fact, their translation of xMLF into F x ι has itself been inspired by the translation of MLF into System F by Leijen and Löh [2005] and Leijen [2007]. However, Manzonetto and Tranquilli restrict their study to the termination of xMLF without any interest in F η or F <: , while our main interest is not in F x ι , but in F p ι and F ι , i.e.…”

Section: Related Workmentioning

confidence: 99%

On the power of coercion abstraction

Cretin

Rémy

2012

SIGPLAN Not.

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Erasable coercions in System F-eta, also known as retyping functions, are well-typed eta-expansions of the identity. They may change the type of terms without changing their behavior and can thus be erased before reduction. Coercions in F-eta can model subtyping of known types and some displacement of quantifiers, but not subtyping assumptions nor certain forms of delayed type instantiation. We generalize F-eta by allowing abstraction over retyping functions. We follow a general approach where computing with coercions can be seen as computing in the lambda-calculus but keeping track of which parts of terms are coercions. We obtain a language where coercions do not contribute to the reduction but may block it and are thus not erasable. We recover erasable coercions by choosing a weak reduction strategy and restricting coercion abstraction to value-forms or by restricting abstraction to coercions that are polymorphic in their domain or codomain. The latter variant subsumes F-eta, F-sub, and MLF in a unified framework.

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A type directed translation of MLF to system F

Cited by 5 publications

References 11 publications

FreezeML: Complete and Easy Type Inference for First-Class Polymorphism

FreezeML: Complete and Easy Type Inference for First-Class Polymorphism

Equality Saturation: A New Approach to Optimization

On the power of coercion abstraction

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